Floating search methods in feature selection
Pattern Recognition Letters
Data mining: concepts and techniques
Data mining: concepts and techniques
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Feature Selection for Knowledge Discovery and Data Mining
Feature Selection for Knowledge Discovery and Data Mining
Nonparametric selection of input variables for connectionist learning
Nonparametric selection of input variables for connectionist learning
Grafting: fast, incremental feature selection by gradient descent in function space
The Journal of Machine Learning Research
k-nearest neighbors directed noise injection in multilayer perceptron training
IEEE Transactions on Neural Networks
Efficient training of RBF neural networks for pattern recognition
IEEE Transactions on Neural Networks
Estimating optimal feature subsets using efficient estimation of high-dimensional mutual information
IEEE Transactions on Neural Networks
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This paper focuses on enhancing the effectiveness of filter feature selection models from two aspects. One is to modify feature searching engines based on optimization theory, and the other is to improve the regularization capability using point injection techniques. The second topic is undoubtedly important in the situations where overfitting is likely to be met, for example, the ones with only small sample sets available. Synthetic and real data are used to demonstrate the contribution of our proposed strategies.